Determining a dynamic user profile indicative of a user behavior context with a mobile device

ABSTRACT

Methods, apparatuses and articles of manufacture for use in a mobile device to determine whether a dynamic user profile is to transition from a first state to a second state based, at least in part, on one or more sensed indicators. The dynamic user profile may be indicative of one or more current inferable user behavior contexts for a user co-located with the mobile device. The mobile device may transition a dynamic user profile from a first state to a second state, in response to a determination that the dynamic user profile is to transition from the first state to the second state, and operatively affect one or more functions performed, at least in part, by the mobile device based, at least in part, on the transition of the dynamic user profile to the second state.

This patent application claims benefit of and priority to U.S.Provisional Patent Application 61/432,538, filed Jan. 13, 2011, entitled“Improving Semantic Place Identification”, and which is herebyincorporated by reference.

BACKGROUND

1. Field

The subject matter disclosed herein relates to electronic devices, andmore particularly to methods, apparatuses and articles of manufacturefor use in a mobile device to determine a dynamic user profile that maybe indicative of a current inferable user behavior context.

2. Information

The Global Positioning System (GPS) represents one type of GlobalNavigation Satellite System (GNSS), which along with other types ofsatellite positioning systems (SPS) provide or otherwise supportsignal-based position location capabilities (e.g., navigation functions)in mobile devices. Location based services in a wireless networktypically rely on GPS and/or indoor positioning technologies forobtaining estimates of locations of mobile devices. Such mobile devices,for example, may include circuitry and/or logic capable of processingsignals received from transmitters to measure ranges to suchtransmitters. With such range measurements and knowledge of thelocations of the transmitters, a location of such a mobile device may beestimated using well known techniques.

In particular implementations, a mobile device may be capable ofcommunicating (e.g., wirelessly) with a centralized location serveroperating as part of a navigation system to provide location basedservices. Such a location server may communicate with a mobile device toreceive, for example, estimates of location of the mobile device and/orinformation indicative of ranges to transmitters at known location. Alocation server may use such information to track the location of amobile device over time.

In some particular applications, a navigation system may applygeofencing whereby an action may be taken if a mobile device enters aperimeter about a particular point of interest (POI). Here, a boundaryor perimeter about such a POI may be defined at a particular distance toprovide a circle enclosing the POI. Of course, shapes other than acircle may be used for geofencing. In one particular implementation, apromotional message and/or coupon from an establishment may betransmitted to a mobile station by a venue operator if the mobilestation's location moves to within a geofence enclosing theestablishment. Here, it is assumed that if a person traveling with themobile station moves to within such a geofence boundary, there is asubstantial likelihood that the person will imminently pass by orapproach the particular point of interest.

Typical geofencing applications may be premised on the notion that if amobile device user is proximate to a point of interest, there is asubstantial likelihood that the user is interested in the point ofinterest, and may likely take a particular action with respect to thePOI. A simple geofencing operation associating individuals to a POImerely by being within a geofence boundary, however, may not fullyappreciate a relationship of an individual with a proximate orgeographically close POI.

SUMMARY

In accordance with an example aspect, a method may comprise, at a mobiledevice: determining whether a dynamic user profile is to transition froma first state to a second state based, at least in part, on one or moresensed indicators, the dynamic user profile being indicative of acurrent inferable user behavior context for a user co-located with themobile device; transitioning the dynamic user profile from the firststate to the second state in response to a determination that thedynamic user profile is to transition from a first state to a secondstate; and operatively affecting one or more functions performed, atleast in part, by the mobile device based, at least in part, on thetransition of the dynamic user profile from the first state to thesecond state.

In accordance with another example aspect, an apparatus for use in amobile device may comprise: means for determining whether a dynamic userprofile is to transition from a first state to a second state based, atleast in part, on one or more sensed indicators, the dynamic userprofile being indicative of a current inferable user behavior contextfor a user co-located with the mobile device; means for transitioningthe dynamic user profile from the first state to the second state, inresponse to a determination that the dynamic user profile is totransition from a first state to a second state; and means foroperatively affecting one or more functions performed, at least in part,by the mobile device based, at least in part, on the transition of thedynamic user profile from the first state to the second state.

In accordance with yet another example aspect, a mobile device maycomprise: memory; and a processing unit to: determine whether a dynamicuser profile is to transition from a first state to a second statebased, at least in part, on one or more sensed indicators in the memory,the dynamic user profile being indicative of a current inferable userbehavior context for a user co-located with the mobile device;transition the dynamic user profile from the first state to the secondstate, in response to a determination that the dynamic user profile isto transition from a first state to a second state; and operativelyaffect one or more functions performed, at least in part, by the mobiledevice based, at least in part, on the transition of the dynamic userprofile from the first state to the second state.

In accordance with still another example aspect, an article ofmanufacture may comprise: a non-transitory computer-readable mediumhaving stored therein computer-readable instructions executable by oneor more processing units in a mobile device to: determine whether adynamic user profile is to transition from a first state to a secondstate based, at least in part, on one or more sensed indicators, thedynamic user profile being indicative of a current inferable userbehavior context for a user co-located with the mobile device;transition the dynamic user profile from the first state to the secondstate, in response to a determination that the dynamic user profile isto transition from a first state to a second state; and operativelyaffect one or more functions performed, at least in part, by the mobiledevice based, at least in part, on the transition of the dynamic userprofile from the first state to the second state.

BRIEF DESCRIPTION OF DRAWINGS

Non-limiting and non-exhaustive aspects are described with reference tothe following figures, wherein like reference numerals refer to likeparts throughout the various figures unless otherwise specified.

FIG. 1 is a schematic block diagram illustrating an example environmentcomprising a mobile device that may determine a dynamic user profilethat may be indicative of a current inferable user behavior context fora user, in accordance with an implementation.

FIG. 2 is a schematic block diagram illustrating certain features of anexample computing platform in the form of a mobile device to determine adynamic user profile that may be indicative of a current inferable userbehavior context for a user, in accordance with an implementation.

FIG. 3 is a flow diagram illustrating certain features of an exampleprocess or method for use in a mobile device to determine a dynamic userprofile that may be indicative of a current inferable user behaviorcontext for a user, in accordance with an implementation.

DETAILED DESCRIPTION

A person's behavior tends to vary from time to time depending on avariety of factors. For example, a person's behavior may vary from timeto time with regard to one or more points of interest (e.g., locations,venues, places, entities, businesses, structures, objects, etc.), one ormore activities (e.g., working, vacationing, exercising, commuting,caring for children, attending to certain errands, shopping, driving,walking, etc.), one or more time periods (e.g., time of day, day ofweek, date, working hours, non-working hours, etc.), and/or the like orsome combination thereof.

Since one or more functions performed, at least in part, by a mobiledevice may be of possible use or assistance to a person (user), it maybe beneficial for a mobile device to identify a current user behaviorcontext and to possibly affect one or more functions that may or may notbe of current use to the user. Depending on a current user behaviorcontext, for example, it may be useful to affect an operation of variouslocation based service functions, position location functions,navigation functions, network communication functions, user outputfunctions, and/or the like or some combinations thereof.

With this in mind, various techniques are described herein which may beimplemented in a mobile device to inferentially identify a current userbehavior context with regard to a user of a mobile device based, atleast in part, on one or more sensed indicators obtained by the mobiledevice. For example, certain sensed indicators may be based, at least inpart, on one or more wireless signals received from one or more otherdevices, one or more sensed inertial movements of the mobile device, oneor more sensed environmental measurements, one or more encoded audiosignals, one or more encoded images, and/or the like or some combinationthereof. In certain examples, one or more sensed indicators may bebased, at least in part, on an estimated position location of the mobiledevice, an estimated future destination of the mobile device, anestimated route of travel of the mobile device, and/or the like or somecombination thereof. In still other examples, one or more sensedindicators may be based, at least in part, on various data files, suchas one or more user schedule files, one or more user communicationfiles, one or more user preference files, and/or the like or somecombination thereof.

Thus, in certain example implementations, a mobile device may determinea dynamic user profile that may be indicative of a current inferableuser behavior context for a user co-located with the mobile device, andoperatively affect one or more functions based, at least in part, on thedynamic user profile. More specifically, in certain exampleimplementations a mobile device may determine whether a dynamic userprofile is to transition from a first state to a second state based, atleast in part, on one or more sensed indicators. Such a mobile devicemay, for example, transition the dynamic user profile from the firststate to the second state in response to a determination that thedynamic user profile is to transition from a first state to a secondstate, and operatively affect one or more functions performed, at leastin part, by the mobile device based, at least in part, on the transitionof the dynamic user profile from the first state to the second state.

Thus, in certain example implementations, a mobile device may establishand/or maintain one or more patterns or models of behavior associatedwith various states. Hence, for example, a mobile device may determinewhether a dynamic user profile is to transition from a first state to asecond state based, at least in part, on whether one or more sensedindicators sufficiently “matches” a particular stored pattern or modelof behavior previously associated with a first state, a second state,and/or some other state of the dynamic user profile.

By way of example, a dynamic user profile may be associated with a pointof interest (POI) such as a business office, a store, a restaurant,etc., that a user and co-located mobile device may be at or nearby. Auser may have differing roles (e.g., purposes, intentions, etc.) withregard to such POI and hence exhibit different behaviors and/or performdifferent activities from time to time with regard to such POI. Forexample, a user may visit a particular POI from time to time as avisitor, a client, a customer, etc. As such, for example, a dynamic userprofile may indicate such user behavior as a first state. One or moresensed indicators may, for example, be considered to determine that thedynamic user profile is in or will be transitioning to such a firststate. Hence, with the dynamic user profile being in a first state afunction such as a location based service function may operate toprovide a user with additional information (e.g., an advertisement, adiscount coupon, etc.) that may be of interest to the user regarding thePOI, and/or some other possibly competing or otherwise related POI.However, the same user may also visit the same POI at other times as aworker (e.g., a volunteer, an employee, etc.). As such, for example, adynamic user profile may indicate such user behavior as a second state.One or more sensed indicators may, for example, be considered todetermine that the dynamic user profile is in or will be transitioningto a second state. Hence, in response to a transition of the dynamicuser profile to such a second state, a function such as theabove-mentioned location based service function may be operativelyaffected in some manner. For example, a user may not be interested inreceiving certain additional information regarding a particular POI,and/or some other possibly competing or otherwise related POI, while atwork at the particular POI, or even while commuting to or from work atthe particular POI.

By way of example, a dynamic user profile may have different statesdepending, at least in part, on differences relating to one or more useractivities. For example, a user activity of driving an automobile may beassociated with different states. For example, a dynamic user profilemay indicate that a user may be commuting to or from work as a firststate, to or from a child's school as a second state, to a hospital(e.g., for an emergency, appointment, etc.) as a third state, to aparticular destination (e.g., second home, vacation spot, etc.) as afourth state, etc. In certain instances, for example, one or more statesof a dynamic user profile may indicate that a user may be driving orriding in a particular automobile and/or other type of vehicle ortransportation mechanism (e.g., bus, train, boat, airplane, etc.). Incertain instances, for example, one or more states of a dynamic userprofile may indicate that a user may or may not be accompanied bycertain other people, e.g., with or without one or more children, etc.For example, it may be determined that a user is with a particularperson based on a signals received from a mobile device carried by theother person, by a schedule or calendar entry, by sounds recorded usinga microphone, etc. One or more sensed indicators may, for example, beconsidered to determine that the dynamic user profile is in or will betransitioning to a particular state. Hence, in response to a transitionof the dynamic user profile to a particular state, one or more functionsmay be operatively affected in some manner. For example, a user may ormay not be interested in receiving certain additional information from alocation based service function and/or other function(s) while attendingto certain errands, such as, driving a child to school in the morningand/or driving to the school to pick up the child from school later thatsame day. For example, a user may or may not be interested in receivingcertain additional information from a location based service functionand/or other function(s) while attempting to drive directly to anemergency room of a hospital, an airport, an upcoming appointment ormeeting, etc. For example, while a user may be interested in receivingcertain additional information from a location based service functionand/or other function(s) while driving in a particular vehicle, they maynot be as interested in such additional information while riding as apassenger on a train or bus. Similarly, for example, while a user may beinterested in receiving certain additional information from a locationbased service function and/or other function(s) while walking orstrolling at or nearby a particular POI, the user may not be asinterested in such additional information while exercising (e.g.,running, bicycling, etc.) at or nearby such particular POI. Likewise,for example, while a user may be interested in receiving certainadditional information from a location based service function and/orother function(s) while alone or with other adults, the user may not beas interested in such additional information while caring for a child,other people, or animals. For example, a user may not be interested inreceiving information relating to a cigar shop while caring for a childor walking a dog.

As alluded to in the various examples above, a dynamic user profile mayhave different states depending, at least in part, on different periodsof time. For example, a user may have differing roles (e.g., purposes,intentions, etc.) with regard to a POI and/or an activity based on atime of day, a day of week, a date, etc., and hence exhibit differentbehaviors at different times. For example, a dynamic user profile mayhave different states depending on periods of time associated with ascheduled, planned, or otherwise identifiable or reoccurring event, suchas, e.g., a workday, a lunch break, a meal time, a weekend, a vacationday, a holiday, a birthday, an exercise class, an appointment, a commutetime, a religious service, an arrival or departure time, a theater orgame time, hours of operation of a POI, a particular starting or endingtime relating to an event or object, and/or the like or some combinationthereof. For example, while a user may have abundant time to shop forgroceries on a weekend, the same user may have relatively less time topurchase a few selected items at the grocery store on a weekday whilecommuting home from work. As another example, a user traveling to anexercise class may not be as interested in receiving informationrelating to a donut shop, a tavern, or cigar shop. Additionally, forexample, a user who appears to have recently obtained a morning coffeefrom a first coffee shop or at home (e.g., from an appliance) prior toor while commuting to work, may not be as interested in receiving atime-limited coupon for a coffee from another vendor during theremainder of their commute.

With the preceding examples in mind, example data processing techniquesare provided below which may be implemented as various methods,apparatuses, or otherwise provided in articles of manufacture for use bya mobile device that may comprise or take the form of a special purposecomputing platform to determine whether a dynamic user profile is totransition from one state to another state based, at least in part, onone or more sensed indicators, and wherein the dynamic user profile maybe indicative of a current inferable user behavior context for a userco-located with the mobile device.

FIG. 1 is a schematic block diagram illustrating an example environment100 comprising an example mobile device 102 comprising an apparatus 116that may be used to determine whether a dynamic user profile is totransition from one state to another state, transition the dynamic userprofile accordingly, and operatively affect one or more functions 118performed, at least in part, by mobile device 102, in accordance with animplementation. As illustrated, environment 100 may also comprise one ormore networks 104, one or more other devices 106, and one or moretransmitting devices 110, all or some of which may be operativelycoupled together via one or more wireless and/or wired communicationlinks. In certain example instances, transmitting devices 110 maytransmit one or more wireless signals 111 that may be received by anetwork interface 114 and/or one or more location receivers 124 ofmobile device 102. In certain example instances, other devices 106 maytransmit one or more wireless signals 107 that may be received bynetwork interface 114 of mobile device 102, and/or receive one or morewireless signals 107 that may be transmitted by network interface 114.In certain example instances, other devices 106 may transmit one or moresignals over a wired communication link with network(s) 104, and/orreceive one or more signals over a wired communication link withnetwork(s) 104. In certain example instances, network(s) 104 maytransmit one or more wireless signals 105 that may be received bynetwork interface 114 of mobile device 102, and/or receive one or morewireless signals 107 that may be transmitted by network interface 114.

By way of example, mobile device 102 may comprise any electronic devicethat may be moved about by a user and which comprises a networkinterface 114 for receiving signals transmitted by transmitting devices110 (e.g., access points, cell towers, beacons, satellites, etc.) and/orother resources in network(s) 104, etc. Thus, by way of some examples,mobile device 102 may comprise a cell phone, a smart phone, a computer(e.g., a personal computer such as a laptop computer, a tablet computer,a wearable computer, etc.), a navigation aid, a digital book reader, agaming device, a music and/or video player device, a camera, etc.

Apparatus 116 is representative of circuitry, such as, e.g., hardware,firmware, a combination of hardware and software, and/or a combinationof firmware and software or other like logic that may be provided inmobile device 102 and used, at least in part, to determine whether adynamic user profile is to transition from one state to another state,transition the dynamic user profile accordingly, and operatively affectone or more functions 118 performed, at least in part, by mobile device102. Functions 118 may, for example, be representative of one or morelocation based service functions, one or more position locationfunctions, one or more navigation functions, one or more networkcommunication functions, one or more user output functions, and/or thelike or some combination thereof.

In certain example implementations, mobile device 102 may functionexclusively or selectively as a stand-alone device, and may provide aone or more capabilities/services of interest/use to a user. In certainexample implementations, mobile device 102 may communicate in somemanner with one or more other devices 106 directly, or indirectly, e.g.,as illustrated by the wireless/wired communication links using thenetwork(s) 104. Network(s) 104 may be representative of one or morecommunication and/or computing resources (e.g., devices and/or services)which mobile device 102 may communicate with or through, e.g., vianetwork interface 114 using one or more wired or wireless communicationlinks. Thus, in certain instances mobile device 102 may receive (orsend) data and/or instructions via network(s) 104. In certain instances,mobile device 102 may, for example, not only receive a signal from atransmitting device 110, but may also transmit a signal to such atransmitting device (e.g., having a receiver).

In certain example implementations, mobile device 102 may be enabled toreceive signals associated with one or more wireless communicationnetworks, location services, and/or the like or any combination thereofwhich may be associated with one or more transmitting devices 110 and/ornetwork(s) 104.

Mobile device 102 may, for example, be enabled (e.g., via networkinterface 114) for use with various wireless communication networks suchas a wireless wide area network (WWAN), a wireless local area network(WLAN), a wireless personal area network (WPAN), and so on. The term“network” and “system” may be used interchangeably herein. A WWAN may bea Code Division Multiple Access (CDMA) network, a Time Division MultipleAccess (TDMA) network, a Frequency Division Multiple Access (FDMA)network, an Orthogonal Frequency Division Multiple Access (OFDMA)network, a Single-Carrier Frequency Division Multiple Access (SC-FDMA)network, and so on. A CDMA network may implement one or more radioaccess technologies (RATs) such as cdma2000, Wideband-CDMA (W-CDMA),Time Division Synchronous Code Division Multiple Access (TD-SCDMA), toname just a few radio technologies. Here, cdma2000 may includetechnologies implemented according to IS-95, IS-2000, and IS-856standards. A TDMA network may implement Global System for MobileCommunications (GSM), Digital Advanced Mobile Phone System (D-AMPS), orsome other RAT. GSM and W-CDMA are described in documents from aconsortium named “3rd Generation Partnership Project” (3GPP). Cdma2000is described in documents from a consortium named “3rd GenerationPartnership Project 2” (3GPP2). 3GPP and 3GPP2 documents are publiclyavailable. A WLAN may include an IEEE 802.11x network, and a WPAN mayinclude a Bluetooth network, an IEEE 802.15x, for example. Wirelesscommunication networks may include so-called next generationtechnologies (e.g., “4G”), such as, for example, Long Term Evolution(LTE), Advanced LTE, WiMAX, Ultra Mobile Broadband (UMB), and/or thelike.

In certain example implementations, mobile device 102 may be enabled,e.g., via network interface 114 or a location receiver 124, for use withvarious location service(s), such as, a Global Navigation SatelliteSystem (GNSS), or other like satellite and/or terrestrial locatingservice, a location based service (e.g., via a cellular network, a WiFinetwork, etc.), and/or the like or some combination thereof.

One or more other devices 106 is illustrated as being connected tomobile device 102 and/or network(s) 104 via one or more networkinterfaces (not shown), which in certain implementations may be similarto network interface 114. Other device 106 may, for example, compriseone or more computing platforms, one or more other mobile devices, oneor more appliances, one or more machines, and/or the like or somecombination thereof.

As described in greater detail below, apparatus 116 may obtain one ormore sensed indicators using network interface 114, one or more locationreceivers 124, one or more inertial sensors 120 (e.g., accelerometers,gyrometers, gyroscopes, etc.), one or more environmental sensors 122(e.g., magnetometers, compass, barometer, thermometer, stress gauge,microphone or other sound transducer, camera or other light sensitivesensors, etc.), and/or the like or some combination thereof.

Also illustrated in FIG. 1 is an estimated position location 130 ofmobile device 102. Estimated position location 130 may, for example,represent a current or recent estimate of a position location of mobiledevice 102 based on one or more signals received from transmittingdevices 110 using network interface 114 and/or location receiver 124.Such location position estimating techniques are well known and may, forexample, be used to identify a coordinate-based location (e.g.,latitude, longitude, altitude, grid point, etc.) relative to a map orother like drawing, and possibly additional motion related information(e.g., heading, velocity, etc.) relative to the recent movement ofmobile device 102. Also, various perceived motion related information(e.g., orientation, heading, velocity, accelerations, decelerations,turns, mode of travel indications, etc.) relative to the recentmovements of mobile device 102 may be obtained based, at least in part,on one or more signals and/or measurements of one or more inertialsensors 120, one or more environmental sensors, and/or the like or somecombination thereof, again using known techniques. Hence, in certainexample implementations, one or more estimated routes of travel 134 toan estimated future destination 132 may be known or determined by mobiledevice 102. As illustrated, estimated position location 130 maycorrespond to a first POI 140-1 (e.g., a home of a user), estimatedfuture destination 132 may correspond to a target POI 140-n (e.g., anoffice building, an airport, a doctor's office, a public venue, anobject, etc.), and an estimated route of travel 134 may pass nearby orpossibly through one or more other POIs represented by POI 140-2. Incertain example implementations, POI 140-2 may represent an intendedintermediate target POI (e.g., an automated teller machine, a day-carefacility or school drop-off/pick-up, etc.) or may represent anunintended POI for which information may or may not be of interest to auser of mobile device 102 (e.g., a coffee shop, oil change business,etc.). Points of interest and route planning may, for example, beprovided in whole or in part by one or more functions performed bymobile device 102 and/or in other computing devices.

FIG. 2 is a schematic block diagram illustrating certain features of anexample computing platform 200 shown in the form of mobile device 102for use in determining whether a dynamic user profile is to transitionfrom one state to another state, transitioning the dynamic user profileaccordingly, and operatively affecting one or more functions performed,at least in part, by mobile device 102, in accordance with animplementation.

As illustrated mobile device 102 may comprise one or more processingunits 202 to perform data processing (e.g., in accordance with thetechniques provided herein) coupled to memory 204 via one or moreconnections 206. Processing unit(s) 202 may, for example, be implementedin hardware or a combination of hardware and software. Processingunit(s) 202 may be representative of one or more circuits configurableto perform at least a portion of a data computing procedure or process.By way of example but not limitation, a processing unit may include oneor more processors, controllers, microprocessors, microcontrollers,application specific integrated circuits, digital signal processors,programmable logic devices, field programmable gate arrays, or the like,or any combination thereof.

Memory 204 may be representative of any data storage mechanism. Memory204 may include, for example, a primary memory 204-1 and/or a secondarymemory 204-2. Primary memory 204-1 may comprise, for example, a randomaccess memory, read only memory, etc. While illustrated in this exampleas being separate from the processing units, it should be understoodthat all or part of a primary memory may be provided within or otherwiseco-located/coupled with processing unit(s) 202, or other like circuitrywithin mobile device 102. Secondary memory 204-2 may comprise, forexample, the same or similar type of memory as primary memory and/or oneor more data storage devices or systems, such as, for example, a diskdrive, an optical disc drive, a tape drive, a solid state memory drive,etc. In certain implementations, secondary memory may be operativelyreceptive of, or otherwise configurable to couple to, computer-readablemedium 250. Memory 204 and/or computer-readable medium 250 may compriseinstructions 252 associated with data processing, e.g., in accordancewith the techniques and/or apparatus 116 (FIG. 1), as provided herein.It will be understood that the computer-readable medium 250 can compriseany of a variety of non-transitory computer-readable media, includingstorage devices or systems similar to those of primary memory 204-1and/or secondary memory 204-2 described above.

Mobile device 102 may, for example, further comprise one or more userinput devices 208, one or more output devices 210, one or more networkinterfaces 114, one or more location receivers 124, one or more inertialsensors 120, and/or one or more environmental sensors 122. Asillustrated, in certain example implementations, an environmental sensor122 may comprise a camera 122-1 or some other form of a light sensitivesensor 122-2, a microphone 122-3, and/or the like or some combinationthereof, which in certain instances may also take the form of an inputdevice.

Input device(s) 208 may, for example, comprise various buttons,switches, a touch pad, a trackball, a joystick, a touch screen, amicrophone, a camera, and/or the like, which may be used to receive oneor more user inputs. Output devices 210 may, for example, comprisevarious devices that may be used in producing a visual output, anaudible output, and/or a tactile output for a user.

A network interface 114 may, for example, provide connectivity to one ormore transmitting devices 110 and/or network(s) 104 (FIG. 1), e.g., viaone or more communication links. Location receiver 124 may, for example,obtain signals from one or more location services, GPS, etc. (notshown), which may be used in estimating a location of mobile device 102at certain times.

Processing unit(s) 202 and/or instructions 252 may, for example, provideor otherwise be associated with one or more encoded electrical signalsstored in memory 204, such as, apparatus 116, one or more functions 118,a dynamic user profile 220 and a state 222 thereof, one or more sensedindicators 224, a current inferable user behavior context 226, one ormore patterns or models of behavior 228, one or more sensed inertialmovements 230, one or more sensed environmental measurements 232, one ormore encoded audio signals 234, one or more encoded images 236, one ormore encoded data files 238 (e.g., user schedule files, usercommunication files, etc.), and/or the like or any combination thereof,e.g., as described in the various example techniques herein.

FIG. 3 is a flow diagram illustrating certain features of an exampleprocess or method 300 for use at a mobile device 102, in accordance withan implementation.

At example block 302, one or more sensed indicators may be obtained. Forexample, certain sensed indicators may be based, at least in part, onone or more wireless signals received from one or more other devices106, one or more sensed inertial movements 230 of the mobile device, oneor more sensed environmental measurements 232, one or more encoded audiosignals 234, one or more encoded images 236, and/or the like or somecombination thereof. In certain examples, one or more sensed indicatorsmay be based, at least in part, on an estimated position location 130 ofthe mobile device, an estimated future destination 132 of the mobiledevice, an estimated route of travel 134 of the mobile device, and/orthe like or some combination thereof. In still other examples, one ormore sensed indicators may be based, at least in part, on variousencoded data files 234, such as, one or more user schedule files (e.g.,associated with a calendar or other like application, etc.), one or moreuser communication files (e.g., a call log, email log, etc.), one ormore user preference files (e.g., comprising implicitly definedpreferences, learned or inferred preferences, historical records, etc.),and/or the like or some combination thereof.

At example block 304, mobile device 102 may determine whether a dynamicuser profile 220, which is indicative of a current inferable userbehavior context, is to transition from a first state to a second statebased, at least in part, on one or more sensed indicators 224. Forexample, at block 304, a mobile device 102 may determine whether one ormore sensed indicators sufficiently “match” one or more stored patternsor models of behavior previously associated with one or more states 222,and/or if a previously unknown state may be learned and established,e.g., based, at least in part, one or more sensed indicators. In certainexample implementations, a determination at block 304 may comprise adetermination that mobile device 102 may be estimated to within athreshold distance (direct or indirect via some path) of a location of aPOI 140. In certain example implementations, a determination at block304 may comprise a determination that mobile device 102 may be moving ormay have been moved in a particular manner and/or via a particular modeof transportation. In certain example implementations, a determinationat block 304 may comprise a determination that one or more particularother devices may or may not be within a threshold distance of mobiledevice 102. In certain example implementations, a determination at block304 may be based, at least in part, on a current or future time period.In certain example implementations, a determination at block 304 may bebased, at least in part, on one or more patterns or models of behavior228.

At example block 306, one or more patterns or models of behavior 228 maybe accessed or otherwise obtained, maintained, or established for one ormore states 222. For example, a pattern or model of behavior 228 may bebased, at least in part, on one or more sensed indicators. Here, forexample, sensed indicators may relate to certain POIs 140, one or moreperceived user activities, a perceived mode of transportation and/orother movements of mobile device 102, an estimated location position,destination and/or path to travel, certain perceived environmentalchanges, an electronic map or other like encoded data files, a workschedule, a travel schedule, an on-line calendar, an electronicappointment book, a communication log, status information regardingother devices that may be nearby, and/or the like or some combinationthereof. For example, a pattern or model of behavior 228 may be based,at least in part, on one or more encoded data files 238, and/or locationposition and/or other like information from a location receiver 124.

At example block 308, the dynamic user profile may be transitioned asapplicable, e.g., from the first state to the second state. For example,in certain example implementations, a state 222 (encoded data, semanticterminology, bit pattern, etc.) stored in memory may indicate a currentinferable user behavior context of the second state.

At example block 310, one or more functions 118 may be operativelyaffected in some manner based, at least in part, on the transition ofthe dynamic user profile from the first state to the second state. Forexample, an operation of a function may be altered in response to atransition to the second state. For example, an operation of a functionmay be initiated, paused, or halted, in response to a transition to thesecond state.

As illustrated in the various examples herein, in certainimplementations, in addition to determining that a mobile device may beproximate or geographically close to a POI (e.g., by applying ageofence, threshold, etc.), a particular “user behavior context” may beinferred to associate the user with the POI. For example, a POI that isa restaurant may serve multiple different functions such as 1) a placefor purchasing a meal and dining, 2) place of employment (e.g., foremployees of the restaurant), 3) a delivery destination (e.g., for avendor) or 4) a regulated establishment (e.g., for a government healthinspector of alcoholic beverage commission). Likewise, a userapproaching a restaurant may have particular attributes such as any oneof several roles including a regular patron, health inspector, waiter,vendor, etc. Thus, by associating an individual's particular role with afunction of the restaurant, a particular current user behavior contextmay be inferred as the user travels towards, nearby, etc., therestaurant. In this particular example, a current inferable userbehavior context 226 may be indicative of a user's purpose for thevisit. Hence, with a current inferable user behavior context 226 inmind, a location-based service function and/or the like may moreappropriately tailor a specific course of action to be taken in responseto such a user with regard to a POI.

In another particular example, a school building may serve multipledifferent functions such as 1) a place to receive an education, 2) placeof employment, or 3) home. Likewise, a user approaching the schoolbuilding may have particular attributes such as any one of several rolessuch as, for example, a student, teacher, a vendor, a visitor, or acustodian. Again, by associating a user's particular role with afunction of the school building, a particular user behavior context maybe inferred with regard to the school building, the user's activities,and/or a period of time.

In addition to an association of particular user's attributes with oneof multiple different functions of a POI, information such as time ofday, day of week, weather, signals, or other data derived from variousinertial and/or environmental sensors on mobile device 102 may be usedto further infer a particular context in connection with a user beingproximate to or approaching a POI.

In certain example implementations, a current inferable user behaviorcontext 226 may be inferred, at least in part, from signals receivedfrom sensors on a mobile device and a particular semantic context of thePOI. Responsive to an inference of a user's present context, action maybe taken by a mobile device such as, for example, automatically sendingan SMS text message, and/or sounding an alarm, just to name a fewexamples. For example, signals generated by inertial sensors orenvironmental sensors may be associated with one or more known orpreviously observed patterns of behavior. Such a pattern of behavior maybe indicative of being leisurely, in a rush, walking/running, orbehavior indicative of a state of panic, just to name a few examples. Asemantic context of a POI may be defined, at least in part, by aparticular function associated with the POI as discussed above.

In example implementations, various types of information such as networkparameters (e.g., signal strength, number and IDs of network accesspoints or base stations, channel frequencies, etc.), sensor data (e.g.accelerometer, orientation, . . . ), user data (e.g. interaction withdevice, response time), and derived data (e.g. average, standarddeviation, delta of available data) may be associated with a semanticmeaning of a proximate POI such as home, work, daycare, theater, etc. tohelp identification and classification of places and their semanticmeaning Information about wireless networks, sensor data, and userinteraction may be available on mobile devices—the semantic name of aplace may be provided by user annotation or from certain applications.By capturing the mapping of such annotation to a derived place model(e.g. network information, sensor data, user interaction), users'subsequent visits to that place may be more easily and/or moreaccurately identified. Further, semantic meaning of places may be sharedamong users. Identification and classification of places and theirsemantic meaning of the user may help to better understand the user'scontext, activities, and intend. Such information may also be built intothe data model (e.g. user model, location model) for reasoning purposes.A structured representation of this information as part of thecontextual data model may allow for reasoning about the user's contextby also include the places and their semantic meaning.

In another example, responsive to an absence of a match from an attemptto match sensed indicators with a known or previously observed patternsor models of behavior, new patterns or models of behavior may be derivedand stored for use in determining a state of a dynamic user profile atsome point in the future.

In another example implementation, instead of or in addition to behaviorpatterns inferred from sensor signals, a condition or state of anapplication hosted on the mobile device may be associated with asemantic context of a POI for inferring a present context of a user.Such a condition or state of an application may include, for example,being in a voice call, having an email application opened, preparing atext message, and/or playing music, just to name a few examples.Furthermore, a semantic context of a POI may be derived, at least inpart, by a history of user behavior as learned from signals receivedover time from sensors on a mobile device. In one exampleimplementation, a mobile device may take a first action in response toan inferred present context of an individual. A semantic context of aPOI may then be updated based, at least in part, on the individual'sbehavior around or in connection with the POI. A subsequent context ofthe individual relative to the POI may then be inferred based, at leastin part, on the updated context. In response to the subsequent context,the mobile station may take a second action different from the firstaction.

As presented herein, since a user's behavior context may change fromtime to time, such a current behavior context (e.g., a current role,etc.) may be inferred based, at least in part, on one or more sensedindicators. Accordingly, in response to a determined change in theuser's behavior context one or more functions performed or otherwiseprovided via a mobile device may be affected to operate in someparticular manner. One of the examples previously mentioned was that auser's current behavior context may change depending on whether or notthere is be a child with them, e.g., with the user in a role of a parentor guardian of the child.

More specifically, in certain example implementations, a dynamic userprofile that may be indicative of a current inferable user behaviorcontext for a user co-located with the mobile device may be determinedby a mobile device. Since a user's behavior context may change from timeto time as may be inferred, based at least in part, on one more sensedindicators, a dynamic user profile may, at times, transition from onestate to another state. Thus, for example a dynamic user profile maytransition from a first state to a second state based, at least in part,on one or more sensed indicators. In the example parent/guardian andchild example above, a first state may be “without child present” and asecond state may be “with child present”, or some other indications.

In certain example instances, a current inferable user behavior contextmay be based, at least in part, on sensed indicators relating to a POI.In certain example instances, a current inferable user behavior contextmay be based, at least in part, on sensed indicators relating to a useractivity. In certain example instances, a current inferable userbehavior context may be based, at least in part, on sensed indicatorsrelating to a period of time. Thus, for example, in the parent/guardianand child example above: a user may be inferred to be in a particularrole with regard to a determined POI, e.g., “with a child” while atnearby a school, or “without a child” while at a cigar shop; a user maybe inferred to be in a particular role with regard to some determineduser activity, e.g., a “with a child” while driving a school bus, or“without a child” while on a workday lunch break; and/or a user may beinferred to be in a particular role with regard to a particular time,e.g., “with a child” during a scheduled doctor appointment for thechild, or “without a child” while working a factory shift. In certainexample instances, in a parent/guardian and child example above a usermay be inferred to be in a particular role with regard to a determinedPOI, while involved in some determined user activity, and within aparticular time.

Also, as illustrated herein, various sensed indicators may be consideredin determining a dynamic user profile that may be indicative of acurrent inferable user behavior context. For example, in certaininstances, wireless signals may be sensed using a receiver, one or moreinertial and/or environmental sensors may be used, sound and/or lightmay be sensed, and/or an estimated position location, an estimateddestination, and/or an estimated route may be determined via sensedsignals. In certain further examples, a schedule file (e.g., the user'scalendar) and/or a communication file (e.g., a call log) may beprocessed to identify a sensed indicator. Here, for example, in theparent/guardian and child example above, a sensed indicator may relateto a scheduled school pick-up/drop-off event that may be used to infer arole of “with a child” or “without a child,” which may be useful indetermining a user behavior context beyond or in addition to othersensor-based sensed indicators.

As illustrated herein, a mobile device may determine whether a dynamicuser profile is to transition from a first state to a second statebased, at least in part, on one or more sensed indicators. Thus, a roleof a user may be inferred to change at times based on sensed indicatorsand as such it may be beneficial for a mobile device to operatedifferently in response to a determined transition. For example, amobile device may detect that a user who is a coffee drinker may havealready had her coffee, e.g., based on sensed signals from her coffeemaker at home, a sensed stop at some coffee shop POI, or a sensedindicator that she may be late for an appointment, etc. Accordingly, ifa dynamic user profile indicates that the user is a role of a “recentcoffee drinker” then a coupon for a coffee shop may not be presented viathe mobile device, but which might have been presented if a dynamic userprofile indicates that the user is a role of a “thirsty coffee drinker”.

In another example, a dynamic transition may be determined when a usermay likely be late for some scheduled event and appears there is somesensed indications that the user may be “rushing” in their activities,etc., in response to being late. In certain instances, for example, amobile device may operatively affect a coupon delivery function(service) to not deliver a coupon for a coffee shop when a “thirstycoffee drinker” is also inferred to “be in a rush”. Hence, for example,in certain instances, a plurality of dynamic user profiles may beconsidered, and/or a dynamic user profile may be indicative of aplurality states relating to various inferable user behavior contexts.

In yet another example such as a parent/guardian and child example, atransition may dynamically occur when a user's mobile device senses anearby child's mobile device or like tracking device (e.g., viaBluetooth, etc.), or perhaps further based on a sensed car motion (e.g.,via an accelerometer), a sensed calendar event (e.g., a child's doctorappointment), or perhaps a known school drop-off event (e.g., from acalendar, a learned pattern (day of week, time, etc.)), or a combinationthereof, or the like.

Reference throughout this specification to “one example,” “an example,”“certain examples,” or “exemplary implementation” means that aparticular feature, structure, or characteristic described in connectionwith the feature and/or example may be included in at least one featureand/or example of claimed subject matter. Thus, the appearances of thephrase “in one example,” “an example,” “in certain examples,” or “incertain implementations,” or other like phrases in various placesthroughout this specification, are not necessarily all referring to thesame feature, example, and/or limitation. Furthermore, the particularfeatures, structures, or characteristics may be combined in one or moreexamples and/or features.

The methodologies described herein may be implemented by various meansdepending upon applications according to particular features and/orexamples. For example, such methodologies may be implemented inhardware, firmware, and/or combinations thereof, along with software. Ina hardware implementation, for example, a processing unit may beimplemented within one or more application specific integrated circuits(ASICs), digital signal processors (DSPs), digital signal processingdevices (DSPDs), programmable logic devices (PLDs), field programmablegate arrays (FPGAs), processors, controllers, micro-controllers,microprocessors, electronic devices, other devices units designed toperform the functions described herein, and/or combinations thereof.

In the preceding detailed description, numerous specific details havebeen set forth to provide a thorough understanding of claimed subjectmatter. However, it will be understood by those skilled in the art thatclaimed subject matter may be practiced without these specific details.In other instances, methods and apparatuses that would be known by oneof ordinary skill have not been described in detail so as not to obscureclaimed subject matter.

Some portions of the preceding detailed description have been presentedin terms of algorithms or symbolic representations of operations onbinary digital electronic signals stored within a memory of a specificapparatus or special purpose computing device or platform. In thecontext of this particular specification, the term specific apparatus orthe like includes a general purpose computer once it is programmed toperform particular functions pursuant to instructions from programsoftware. Algorithmic descriptions or symbolic representations areexamples of techniques used by those of ordinary skill in the signalprocessing or related arts to convey the substance of their work toothers skilled in the art. An algorithm is here, and generally, isconsidered to be a self-consistent sequence of operations or similarsignal processing leading to a desired result. In this context,operations or processing involve physical manipulation of physicalquantities. Typically, although not necessarily, such quantities maytake the form of electrical or magnetic signals capable of being stored,transferred, combined, compared or otherwise manipulated as electronicsignals representing information. It has proven convenient at times,principally for reasons of common usage, to refer to such signals asbits, data, values, elements, symbols, characters, terms, numbers,numerals, information, or the like. It should be understood, however,that all of these or similar terms are to be associated with appropriatephysical quantities and are merely convenient labels. Unlessspecifically stated otherwise, as apparent from the followingdiscussion, it is appreciated that throughout this specificationdiscussions utilizing terms such as “processing,” “computing,”“calculating,” “determining,” “establishing,” “obtaining,”“identifying,” “maintaining,” and/or the like refer to actions orprocesses of a specific apparatus, such as a special purpose computer ora similar special purpose electronic computing device. In the context ofthis specification, therefore, a special purpose computer or a similarspecial purpose electronic computing device is capable of manipulatingor transforming signals, typically represented as physical electronic ormagnetic quantities within memories, registers, or other informationstorage devices, transmission devices, or display devices of the specialpurpose computer or similar special purpose electronic computing device.In the context of this particular patent application, the term “specificapparatus” may include a general purpose computer once it is programmedto perform particular functions pursuant to instructions from programsoftware.

The terms, “and,” “or,” and “and/or” as used herein may include avariety of meanings that also are expected to depend at least in partupon the context in which such terms are used. Typically, “or” if usedto associate a list, such as A, B or C, is intended to mean A, B, and C,here used in the inclusive sense, as well as A, B or C, here used in theexclusive sense. In addition, the term “one or more” as used herein maybe used to describe any feature, structure, or characteristic in thesingular or may be used to describe a plurality or some othercombination of features, structures or characteristics. Though, itshould be noted that this is merely an illustrative example and claimedsubject matter is not limited to this example.

While there has been illustrated and described what are presentlyconsidered to be example features, it will be understood by thoseskilled in the art that various other modifications may be made, andequivalents may be substituted, without departing from claimed subjectmatter. Additionally, many modifications may be made to adapt aparticular situation to the teachings of claimed subject matter withoutdeparting from the central concept described herein.

Therefore, it is intended that claimed subject matter not be limited tothe particular examples disclosed, but that such claimed subject mattermay also include all aspects falling within the scope of appendedclaims, and equivalents thereof.

What is claimed is:
 1. A method comprising, at a mobile device:determining whether a dynamic user profile is to transition from a firststate to a second state based, at least in part, on one or more sensedindicators, wherein said second state comprises a previously unknownstate, and said dynamic user profile being indicative of a currentinferable user behavior context for a user co-located with said mobiledevice; transitioning said dynamic user profile from said first state tosaid second state in response to a determination that said dynamic userprofile is to transition from said first state to said second state; andoperatively affecting one or more functions performed, at least in part,by said mobile device based, at least in part, on said transition ofsaid dynamic user profile from said first state to said second state. 2.The method as recited in claim 1, wherein determining whether saiddynamic user profile is to transition from said first state to saidsecond state further comprises: determining whether said one or moresensed indicators matches one or more stored patterns or models ofbehavior previously associated with at least said first state; and inresponse to a determination that said one or more sensed indicators doesnot match said one or more stored patterns or models of behaviorpreviously associated with at least said first state, determining thatsaid dynamic user profile is to transition from said first state to saidsecond state.
 3. The method as recited in claim 2, further comprising:establishing and storing one or more new patterns or models of behaviorassociated with said previously unknown state based, at least in part,on said one or more sensed indicators.
 4. The method as recited in claim3, wherein establishing said one or more new patterns or models ofbehavior associated with said previously unknown state furthercomprises: identifying said current inferable user behavior context forsaid user with regard to said second state.
 5. The method as recited inclaim 1, wherein said current inferable user behavior context is based,at least in part, on one or more points of interest.
 6. The method asrecited in claim 1, wherein said current inferable user behavior contextis based, at least in part, on one or more user activities.
 7. Themethod as recited in claim 1, wherein said current inferable userbehavior context is based, at least in part, on one or more timeperiods.
 8. The method as recited in claim 1, wherein at least one ofsaid one or more sensed indicators is based, at least in part, on one ormore wireless signals received from one or more other devices via one ormore network interfaces of said mobile device.
 9. The method as recitedin claim 1, wherein at least one of said one or more sensed indicatorsis based, at least in part, on either or both of: one or more sensedinertial movements of said mobile device from one or more inertialsensors of said mobile device, or one or more sensed environmentalmeasurements from one or more environmental sensors.
 10. The method asrecited in claim 1, wherein at least one of said one or more sensedindicators is based, at least in part, on either or both of: one or moreencoded audio signals recorded using a microphone of said mobile device,or one or more encoded images recorded using a light sensitiveenvironmental sensor of said mobile device.
 11. The method as recited inclaim 1, wherein at least one of said one or more sensed indicators isbased, at least in part, on a current estimated position location ofsaid mobile device.
 12. The method as recited in claim 1, wherein atleast one of said one or more sensed indicators is based, at least inpart, on either or both of: an estimated future destination of saidmobile device, or an estimated route of travel of said mobile device.13. The method as recited in claim 1, wherein at least one of said oneor more sensed indicators is based, at least in part, on either or bothof: one or more user schedule files accessible via said mobile device,or one or more user communication files accessible via said mobiledevice.
 14. The method as recited in claim 1, wherein said one or morefunctions performed, at least in part, by said mobile device comprisesat least one of: one or more location based service functions, one ormore position location functions, one or more navigation functions, oneor more network communication functions, or one or more user outputfunctions.
 15. An apparatus for use in a mobile device, the apparatuscomprising: means for determining whether a dynamic user profile is totransition from a first state to a second state based, at least in part,on one or more sensed indicators, wherein said second state comprises apreviously unknown state, and said dynamic user profile being indicativeof a current inferable user behavior context for a user co-located withsaid mobile device; means for transitioning said dynamic user profilefrom said first state to said second state, in response to adetermination that said dynamic user profile is to transition from saidfirst state to said second state; and means for operatively affectingone or more functions performed, at least in part, by said mobile devicebased, at least in part, on said transition of said dynamic user profilefrom said first state to said second state.
 16. The apparatus as recitedin claim 15, further comprising: means for storing one or more patternsor models of behavior previously associated with at least said firststate; means for determining whether said one or more sensed indicatorsmatches said one or more stored patterns or models of behaviorpreviously associated with at least said first state; and means fordetermining that said dynamic user profile is to transition from saidfirst state to said second state, in response to a determination thatsaid one or more sensed indicators does not match said one or morestored patterns or models of behavior previously associated with atleast said first state.
 17. The apparatus as recited in claim 16,further comprising: means for establishing one or more new patterns ormodels of behavior associated with said previously unknown state based,at least in part, on said one or more sensed indicators.
 18. Theapparatus as recited in claim 17, further comprising: means foridentifying said current inferable user behavior context for said userwith regard to said second state.
 19. The apparatus as recited in claim15, wherein said current inferable user behavior context is based, atleast in part, on one or more points of interest.
 20. The apparatus asrecited in claim 15, wherein said current inferable user behaviorcontext is based, at least in part, on one or more user activities. 21.The apparatus as recited in claim 15, wherein said current inferableuser behavior context is based, at least in part, on one or more timeperiods.
 22. The apparatus as recited in claim 15, further comprising:means for receiving one or more wireless signals from one or more otherdevices; and wherein at least one of said one or more sensed indicatorsis based, at least in part, on at least one received wireless signal.23. The apparatus as recited in claim 15, further comprising: means forsensing one or more inertial movements of said mobile device; andwherein at least one of said one or more sensed indicators is based, atleast in part, on at least one sensed inertial movement of said mobiledevice.
 24. The apparatus as recited in claim 15, further comprising:means for obtaining one or more environmental measurements; and whereinat least one of said one or more sensed indicators is based, at least inpart, on at least one obtained environmental measurement.
 25. Theapparatus as recited in claim 15, further comprising: means forobtaining a current estimated position location of said mobile device;and wherein at least one of said one or more sensed indicators is based,at least in part, on said current estimated position location.
 26. Theapparatus as recited in claim 15, further comprising: means foraccessing either or both of: one or more user schedule files, or one ormore user communication files; and wherein at least one of said one ormore sensed indicators is based, at least in part, on either or both of:at least one of said user schedule files, or at least one of said usercommunication files.
 27. The apparatus as recited in claim 15, whereinsaid one or more functions performed, at least in part, by said mobiledevice comprises at least one of: one or more location based servicefunctions, one or more position location functions; one or morenavigation functions, one or more network communication functions, orone or more user output functions.
 28. A mobile device comprising:memory; and a processing unit to: determine whether a dynamic userprofile is to transition from a first state to a second state based, atleast in part, on one or more sensed indicators in said memory, whereinsaid second state comprises a previously unknown state, and said dynamicuser profile being indicative of a current inferable user behaviorcontext for a user co-located with said mobile device; transition saiddynamic user profile from said first state to said second state, inresponse to a determination that said dynamic user profile is totransition from said first state to said second state; and operativelyaffect one or more functions performed, at least in part, by said mobiledevice based, at least in part, on said transition of said dynamic userprofile from said first state to said second state.
 29. The mobiledevice as recited in claim 28, said processing unit to further:determine whether said one or more sensed indicators matches one or morepatterns or models of behavior stored in said memory and previouslyassociated with at least said first state; and in response to adetermination that said one or more sensed indicators does not matchsaid one or more stored patterns or models of behavior previouslyassociated with at least said first state, determine that said dynamicuser profile is to transition from said first state to said secondstate.
 30. The mobile device as recited in claim 29, wherein saidprocessing unit to further: establish one or more new patterns or modelsof behavior associated with said previously unknown state based, atleast in part, on said one or more sensed indicators; and indicate saidone or more new patterns or models of behavior associated with saidpreviously unknown state to said memory for storage therein.
 31. Themobile device as recited in claim 30, said processing unit to further:identify said current inferable user behavior context for said user withregard to said second state.
 32. The mobile device as recited in claim28, wherein said current inferable user behavior context is based, atleast in part, on one or more points of interest.
 33. The mobile deviceas recited in claim 28, wherein said current inferable user behaviorcontext is based, at least in part, on one or more user activities. 34.The mobile device as recited in claim 28, wherein said current inferableuser behavior context is based, at least in part, on one or more timeperiods.
 35. The mobile device as recited in claim 28, furthercomprising: a network interface; and wherein at least one of said one ormore sensed indicators is based, at least in part, on one or morewireless signals received from one or more other devices via saidnetwork interface.
 36. The mobile device as recited in claim 28, furthercomprising: one or more inertial sensors; and wherein at least one ofsaid one or more sensed indicators is based, at least in part, on one ormore sensed inertial movements of said mobile device from said one ormore inertial sensors.
 37. The mobile device as recited in claim 28,further comprising: one or more environmental sensors; and wherein atleast one of said one or more sensed indicators is based, at least inpart, on one or more sensed environmental measurements from said one ormore environmental sensors.
 38. The mobile device as recited in claim28, further comprising: a location receiver to estimate a currentestimated position location of said mobile device; and wherein at leastone of said one or more sensed indicators is based, at least in part, onsaid current estimated position location of said mobile device.
 39. Themobile device as recited in claim 28, said processing unit to further:determine either or both of an estimated future destination of saidmobile device or an estimated route of travel of said mobile device; andwherein at least one of said one or more sensed indicators is based, atleast in part, on either or both of: said estimated future destinationof said mobile device, or said estimated route of travel of said mobiledevice.
 40. The mobile device as recited in claim 28, wherein at leastone of said one or more sensed indicators is based, at least in part, oneither or both of: one or more user schedule files accessible via saidmemory, or one or more user communication files accessible via saidmemory.
 41. The mobile device as recited in claim 28, wherein said oneor more functions performed, at least in part, by said mobile devicecomprises at least one of: one or more location based service functions,one or more position location functions, one or more navigationfunctions, one or more network communication functions, or one or moreuser output functions.
 42. An article comprising: a non-transitorycomputer-readable medium having stored therein computer-readableinstructions executable by one or more processing units in a mobiledevice to: determine whether a dynamic user profile is to transitionfrom a first state to a second state based, at least in part, on one ormore sensed indicators, wherein said second state comprises a previouslyunknown state, and said dynamic user profile being indicative of acurrent inferable user behavior context for a user co-located with saidmobile device; transition said dynamic user profile from said firststate to said second state, in response to a determination that saiddynamic user profile is to transition from said first state to saidsecond state; and operatively affect one or more functions performed, atleast in part, by said mobile device based, at least in part, on saidtransition of said dynamic user profile from said first state to saidsecond state.
 43. The article as recited in claim 42, saidcomputer-readable instructions being further executable by said one ormore processing units to: determine whether said one or more sensedindicators matches one or more stored patterns or models of behaviorpreviously associated with at least said first state; and determine thatsaid dynamic user profile is to transition from said first state to saidsecond state, in response to a determination that said one or moresensed indicators does not match said one or more stored patterns ormodels of behavior previously associated with at least said first state.44. The article as recited in claim 43, wherein said computer-readableinstructions being further executable by said one or more processingunits to establish one or more new patterns or models of behaviorassociated with said previously unknown state based, at least in part,on said one or more sensed indicators.
 45. The article as recited inclaim 44, said computer-readable instructions being further executableby said one or more processing units to identify said current inferableuser behavior context for said user with regard to said second state.46. The article as recited in claim 42, wherein said current inferableuser behavior context is based, at least in part, on one or more pointsof interest.
 47. The article as recited in claim 42, wherein saidcurrent inferable user behavior context is based, at least in part, onone or more user activities.
 48. The article as recited in claim 42,wherein said current inferable user behavior context is based, at leastin part, on one or more time periods.
 49. The article as recited inclaim 42, wherein at least one of said one or more sensed indicators isbased, at least in part, on at least one received wireless signal. 50.The article as recited in claim 42, wherein at least one of said one ormore sensed indicators is based, at least in part, on at least onesensed inertial movement of said mobile device.
 51. The article asrecited in claim 42, wherein at least one of said one or more sensedindicators is based, at least in part, on at least one sensedenvironmental measurement.
 52. The article as recited in claim 42,wherein at least one of said one or more sensed indicators is based, atleast in part, on a current estimated position location.
 53. The articleas recited in claim 42, wherein at least one of said one or more sensedindicators is based, at least in part, on one or both of: one or moreuser schedule files, or one or more user communication files.
 54. Thearticle as recited in claim 42, wherein said one or more functionsperformed, at least in part, by said mobile device comprises at leastone of: one or more location based service functions, one or moreposition location functions, one or more navigation functions, one ormore network communication functions, or one or more user outputfunctions.